Higher dimensional data sets may be reconstructed from at least two lower dimensional data sets, providing a view from different projection directions. For example, three-dimensional data sets may be reconstructed from two-dimensional projection images. If only sparse information in projection space is available, for example in the case of only a few projection images, objects may be symbolically reconstructed, e.g. not calculating attenuation values for each voxel, but only for example boundaries and/or centerlines of objects. Such reconstruction data sets however, at least provide information on the spatial position and extension of the objects.
Reconstruction from sparse sets of projection images, may be used in diagnostic examinations of blood vessels. Lesions, for example stenosis, may be reconstructed from angiographic projection images. A vessel segment is of interest, that may, for example, be marked/manually segmented in the projection images after a few images are acquired. However, the acquired projection images are often not optimally suited for reconstruction, for example regarding overlapping vessels and/or foreshortening, leading to reconstruction errors and uncertainties in evaluating the data.
An field of application is stenosis in the coronary arteries. To treat arteries constricted by atheromatous plaque, stents are used to restore blood flow. As there are also risks associated with minimally invasive insertion of such stents, only hemodynamically relevant stents are treated. The hemodynamic relevance of a stenosis may be assessed by measuring the fractional flow reserve (FFR). While it is known, for example from an article by Tonino et al., “Fractional Flow Reserve versus Angiography for Guiding Percutaneous Coronary Intervention”, New England Journal of Medicine 360(3), pp. 213-224, 2009, to invasively measure the FFR, it has recently been proposed to measure the FFR non-invasively, e.g. virtually.
The non-invasive, virtual measurement of FFR provides a secure, fast and inexpensive alternative to a measurement by pressure wire. See for example the article by Monique Trobs et al., “Comparison of Fractional Flow Reserve Based on Computational Fluid Dynamics Modeling Using Coronary Angiographic Vessel Morphology Versus Invasively Measured Fractional Flow Reserve”, The American Journal of Cardiology 117 (1), pp. 29-35, 2016. The symbolical reconstruction data set serves as a three-dimensional model, on which computational fluid dynamics (CFD) is performed. The accuracy of the reconstruction is important since the accuracy directly affects the calculation if the FFR and thus the treatment decision.
Reconstruction accuracy is affected by multiple factors. An accurate segmentation of the vessels in the two-dimensional angiographic projection images is necessary. The geometric correlation of the individual angiography scenes may be well estimated that may be impeded by heart and respiratory movement and inaccurate geometrical calibration of the imaging device. The choice of projection directions plays a decisive role. Here, angiographic projection images including a projection direction perpendicular to the vessel segment and a sufficient angle difference to each other are advantageous.
Known reconstruction techniques are based on retrospectively manually choosing suitable angiographic projection images from a preceding acquisition. The acquisition geometries chosen by the medical staff are often not optimal for reconstruction. For example, overlapping vessels may impede segmentation. Furthermore, prospectively shortened (foreshortened) vessel depiction as well as inadequate sets of projection angles may complicate reconstruction.
A workflow is based on using already acquired angiographic projection images and selecting a subset to reconstruct the data set, for example a three-dimensional model. As an example, it is referred to “IZ3D” reconstruction software. The disadvantage of the systems is that the user has to work with data already acquired in acquisition geometries not optimized for reconstruction or acquire additional angiographic projection images, increasing radiation and contrast agent exposure. Additionally, in the workflow, the sequential angiographic projection scenes are acquired independently from each other. In the process, information may be lost.
It has been proposed in not yet laid open patent application DE 10 2016 210 003.3 to acquire additional angiographic projection images in predetermined angular increments along a circular trajectory defined by a rotation axis. The rotation axis is estimated from a first, single angiographic projection image.